Genetic Polymorphisms of the Telomerase Reverse Transcriptase Gene in Relation to Prostate Tumorigenesis, Aggressiveness and Mortality: A Cross-Ancestry Analysis

Simple Summary Mutation in telomerase reverse transcriptase (TERT) has been reportedly related to risks of prostate cancer (PCa). However, prior genome-wide association studies (GWAS) were limited to inconsistency, small-scale, one-outcome phenotype, or single ancestry. In this study, we used two large-scale population datasets from European and Chinese ancestries to comprehensively estimate the association of TERT loci polymorphisms with prostate tumorigenesis and severity. Results of this study showed that (1) over half of the risk variants were located at the intron 2 region in both populations; (2) seven novel loci situated at intron 2, intron 6, intron 9, and intron 12 were first identified to be related to PCa risk; (3) SNPs rs2736100 and rs2853677 were significantly associated with aggressive PCa, whereas rs35812074 was marginally related to PCa death; (4) most identified loci were different between Europeans and Chinese. These findings support the evidence regarding TERT polymorphisms in relation to PCa risk and prognosis, and indicate the heterogeneous genetic architectures of PCa susceptibility loci among distinct ancestries. Abstract Background: Telomerase reverse transcriptase (TERT) has been consistently associated with prostate cancer (PCa) risk. However, few studies have explored the association between TERT variants and PCa aggressiveness. Methods: Individual and genetic data were obtained from UK Biobank and a Chinese PCa cohort (Chinese Consortium for Prostate Cancer Genetics). Results: A total of 209,694 Europeans (14,550 PCa cases/195,144 controls) and 8873 Chinese (4438 cases/4435 controls) were involved. Nineteen susceptibility loci with five novel ones (rs144704378, rs35311994, rs34194491, rs144020096, and rs7710703) were detected in Europeans, whereas seven loci with two novel ones (rs7710703 and rs11291391) were discovered in the Chinese cohort. The index SNP for the two ancestries was rs2242652 (odds ratio [OR] = 1.16, 95% confidence interval [CI]:1.12–1.20, p = 4.12 × 10−16) and rs11291391 (OR = 1.73, 95%CI:1.34–2.25, p = 3.04 × 10−5), respectively. SNPs rs2736100 (OR = 1.49, 95%CI:1.31–1.71, p = 2.91 × 10−9) and rs2853677 (OR = 1.74, 95%CI:1.52–1.98, p = 3.52 × 10−16) were found significantly associated with aggressive PCa, while rs35812074 was marginally related to PCa death (hazard ratio [HR] = 1.61, 95%CI:1.04–2.49, p = 0.034). Gene-based analysis showed a significant association of TERT with PCa (European: p = 3.66 × 10−15, Chinese: p = 0.043) and PCa severity (p = 0.006) but not with PCa death (p = 0.171). Conclusion: TERT polymorphisms were associated with prostate tumorigenesis and severity, and the genetic architectures of PCa susceptibility loci were heterogeneous among distinct ancestries.


Introduction
Prostate cancer (PCa) has become the second most common male cancer and the fifth leading cause of male cancer death worldwide based on the estimated number from GLOBOCAN 2020 [1]. The incidence and mortality of PCa have been increasing in past decades. In the US, PCa incidence increases by 3% annually, with an estimated 288,300 new cases and 34,700 deaths expected in 2023 [2]. In European countries, the estimated new cases and deaths were 473,300 and 108,100, respectively, in 2020 [3]. In China, up to 125,646 new cases and 56,239 deaths were reported in 2022 [4]. To date, only a few risk factors for PCa have been established. Among them, genetic susceptibility is one of the most critical risk factors.
Telomerase, a ribonucleoprotein complex to prevent telomere shortening, is essential for maintaining chromosomal integrity and stability during cell division. Telomerase reverse transcriptase (TERT), a key determinant of the enzymatic activity of telomerase, is reportedly related to both aging and carcinogenesis [5]. Thus, mutations in the TERT regions (5p15.33) in relation to tumorigenesis have long intrigued researchers. Prior genome-wide association studies (GWAS) have found polymorphisms in TERT were associated with risks of multiple cancers, such as breast, lung, glioma, bladder, testicular, pancreas, prostate, and skin cancer [6,7]. In prostate cancer, single nucleotide polymorphisms (SNPs), including rs4449583, rs10069690, rs13172201, and rs2736098, were identified to be associated with disease risks in the European population [7], while rs2736100 and rs10069690 were found to be associated in the Chinese population [8]. Results from previous studies were limited to either inconsistency or their small scale. For the validation of PCa-related TERT SNPs in multiple ancestries, only a cross-ancestry meta-analysis found that rs7726159 and rs2736098 were significantly associated with PCa risk in at least two ancestries [7]. Furthermore, there is a research gap on the association of TERT variants with PCa severity and prognosis.
Given a paucity of investigation regarding the genetic architecture of susceptibility loci of prostate tumorigenesis and prognosis across TERT regions in distinct ancestries, we, therefore, utilize two large-scale population datasets from European and Chinese ancestries to validate the association of TERT loci polymorphisms with PCa, PCa aggressiveness, and PCa death, and to explore the genetic heterogeneity effect among distinct ethnic populations. The primary objective of this study is to provide comparable and comprehensive evidence on TERT genetic variations in prostate cancer risk in two different ethnic populations.

Study Population
The study population in this study comprised patients of European and Chinese ancestries. Data from European participants were obtained from the UK Biobank (UKB), a large-scale biomedical database containing a prospective cohort with a wealth of genetic and phenotypic information. Around 0.5 million individuals between 40 and 69 years old were recruited from 2006 to 2010 across the UK [9]. Participants with PCa were recorded through the cancer registry, hospital electronic system and self-report. Data from Chinese participants were obtained from the Chinese Consortium for Prostate Cancer Genetics (ChinaPCa), an ongoing case-control study in which 5000 pathologically diagnosed PCa patients were recruited from the local hospitals in the south-eastern region in mainland China, whereas the 5000 cancer-free controls were recruited from the local community or physical examination centers [10,11]. All participants were collected with informed consent, and the study was approved by the regional ethics committee.

Outcome Phenotype Ascertainment
In UKB, participants were followed up for prostate cancer (C61) and PCa-specific death using records linkage with the regional system of disease surveillance, chronic disease management, and electronic health records (EHRs) based on diagnostic codes from the International Classification of Diseases, 10th revision (ICD-10). Cancer survival time was ascertained from the date of cancer diagnosis to the date of death, loss to follow-up, or 15 November 2022, whichever came first.
In ChinaPCa, malignant neoplasm of the prostate was ascertained by pathological diagnosis from the local hospital. Aggressive PCa was defined as PCa with Gleason score (GS) ≥ 8 or prostate-specific antigen (PSA) value > 20 ng/mL according to the National Comprehensive Cancer Network (NCCN) guideline.

SNPs Selection and Genotyping
To ensure the probable regulatory regions of the TERT were included, we extended the upstream and downstream of the initial gene region to 100 kb. SNPs located at chr5:1,150,000-1,400,000 were selected according to the HapMap database. Germline DNA samples of the two datasets were extracted from blood samples via whole blood genomic DNA extraction kit and were further genotyped by using the UK Biobank Axiom array in the UKB dataset [12] and Illumina Human OmniExpress BeadChips in the ChinaPCa dataset [10].

Phasing, Imputation and Quality Control
Pre-phasing and imputation in UKB genotyping data were performed via the SHAPEIT and IMPUTE4 program using the Haplotype Reference Consortium and the merged UK10K and 1000 Genome Phase III reference panels [12]. For ChinaPCa genotyping data, pre-phasing analysis was conducted by Eagle v2.4, and imputation was performed using the Michigan Imputation Server using the minimac4 imputation algorithm [13]. Although different imputation algorithms were used on two populations, the imputation accuracy of these two algorithms was deemed highly consistent in accordance with previous research [13]. A posterior probability of >0.90 was applied to call genotypes during the course of imputation. Poorly imputed SNPs were further excluded on the basis of (a) genotype call rate less than 95%, (b) minor allele frequency (MAF) below 0.01, and (c) p-value for the Hardy-Weinberg Equilibrium (HWE) test amid controls lower than 1.0 × 10 −6 .

Statistical Analysis
The association of each SNP with PCa and aggressive PCa was estimated by odds ratio (OR), 95% CI, and corresponding p-value, using logistic regression analysis with adjustment for age based on an additive model. The association of each SNP with PCa death for the UKB sample was estimated by hazard ratio (HR), 95% confidence interval (CI) and corresponding p-value, using Cox regression analysis with adjustment for age, family history, and Charlson Comorbidity Index (CCI), based on an additive model. In order to evaluate the combined effect of the significant SNPs on PCa risk, a polygenic risk score (PRS) was additionally calculated by summing the number of each significant risk allele carried (0, 1, or 2) for each individual, with every single variant weighted by its effect size (log [OR] for binary traits). Gene-based analysis was performed based on the remission and percentage improvement GWAS p-values using MAGMA v1.10 software [14]. The analysis was conducted according to genetic variants and linkage disequilibrium (LD) in two ethnic reference data sets (1000 Genomes European panel and 1000 Genomes East Asian panel), and then SNPs were assigned to genes using the MAGMA NCBI37.3.gene.loc file with a 10-kb window. The gene-based association was estimated using Z statistics and the corresponding p-value. Regional plots were generated from LocusZoom (http://csg.sph.umich.edu/locuszoom/ (accessed on 20 March 2023)). LD heatmap was created using LDBlockShow v1.39 software [15]. All statistical analyses were performed under PLINK v1.90 software. Two-tailed Bonferroni corrected p < 7.35 × 10 −4 (0.05/68) for UKB and p < 5.32 × 10 −4 (0.05/94) for ChinaPCa were considered statistically significant, while the p-value between Bonferroni correction and 0.05 was deemed marginally significant on SNP association analysis. A two-tailed p < 0.05 was considered significant in gene-based analysis.

Participant Characteristics
A total of 209,694 Europeans (14,550 PCa cases/195,144 controls) and 8873 Chinese (4438 cases/4435 controls) were involved in this study (Table 1). Briefly, PCa patients were of older age and had a higher proportion of a positive PCa family history in both populations. The median comorbidity index was higher in Europeans with PCa than in controls (median CCI: 2.0 vs. 0.0, p < 0.001). In the Chinese population, PCa patients had an elevated PSA value compared with their control counterparts (median PSA value: 21.8 vs. 9.8 ng/mL, p < 0.001). 52.1% and 37.6% of the cancer patients had high levels of PSA (>20 ng/mL) and GS (≥8), respectively.

Associations between TERT SNPs and Aggressive PCa Risk
Two TERT SNPs were found to be significantly associated with aggressive PCa risk among PCa cases sample from Chinese ancestry ( Figure 1C   1.28-2.31, p = 3.08 × 10 −4 for Chinese), among which, the first SNP was located in the promoter region whereas the latter two were situated in intron 2 region (Figure 2).

Associations between TERT SNPs and PCa Death
One SNP, rs35812074, was identified to be marginally related to PCa death among PCa cases sample from European ancestry ( Figure 1D). The risk allele (C) of rs35812074 was associated with a 61% increased risk of PCa death (HR = 1.61, 95%CI: 1.04-2.49, p = 0.034) with adjustment for age, family history and comorbidity index (Figure 3).

Gene-Based Analysis
Gene-based analysis using 56 SNPs from European ancestry and 79 SNPs from Chinese ancestry showed that TERT was significantly associated with PCa among the two ancestries (Z = 7.78, p = 3.66 × 10 −15 for European; Z = 1.72, p = 0.043 for Chinese). This gene was also found to be related to aggressive PCa (Z = 2.54, p = 0.006). However, we did not observe a gene-based association between TERT and PCa death (Z = 0.95, p = 0.171) ( Table 4).

Associations between TERT SNPs and PCa Death
One SNP, rs35812074, was identified to be marginally related to PCa death among PCa cases sample from European ancestry ( Figure 1D). The risk allele (C) of rs35812074 was associated with a 61% increased risk of PCa death (HR = 1.61, 95%CI: 1.04-2.49, p = 0.034) with adjustment for age, family history and comorbidity index (Figure 3).

Gene-Based Analysis
Gene-based analysis using 56 SNPs from European ancestry and 79 SNPs from Chinese ancestry showed that TERT was significantly associated with PCa among the two ancestries (Z = 7.78, p = 3.66 × 10 −15 for European; Z = 1.72, p = 0.043 for Chinese). This gene was also found to be related to aggressive PCa (Z = 2.54, p = 0.006). However, we did not observe a gene-based association between TERT and PCa death (Z = 0.95, p = 0.171) ( Table  4).  Table 4.
Gene-based association between TERT and prostate cancer in European and Chinese ancestries.

Discussion
The present study including two ethnic population datasets shows that polymorphisms in TERT are associated with prostate tumorigenesis, aggressiveness, and PCa death. This study is the first to comprehensively illustrate the genetic architectures of PCa susceptibility loci across the TERT region among distinct ancestries. Specifically, we found that (1) over half of the variants significantly associated with PCa risk or aggressiveness were located at the intron 2 region in both populations; (2) seven novel loci situated at intron 2, intron 6, intron 9 and intron 12 were first identified to be related to PCa risk; (3) rs35812074 located in intron 9 was observed marginally associated with PCa death.
TERT, located at 5p15.33 with 16 exons and 15 introns, has been reported to harbor several susceptibility loci that could influence prostate carcinogenesis. A fine-mapping study using 22,301 PCa cases and 22,320 controls identified multiple risk loci, including rs2853669, rs2853676, rs7725218, and rs2242652, which were situated at the promoter, intron 2, intron 3, and intron 4 regions, respectively [16]. Another recent fine-mapping study using European ancestry population additionally found that rs2853677, rs11414507, rs7705526, and rs35334674 at the intron 2 region, rs10069690 at intron 4 region, as well as rs35033501 at exon 16 region were significant SNPs related to PCa risk [17]. Several susceptibility loci, such as rs7712562 at the promoter region and rs7726159 at the intron 3 region, were identified by some case-control studies [18,19]. In this study, we confirmed the aforementioned SNPs to be associated with PCa.
To the best of our knowledge, the present study was the first to comprehensively evaluate the effect of polymorphisms across the TERT on PCa severity and PCa-specific death. SNP rs2736100, located in intron 2, was found to be associated with significant PCa aggressiveness in our study, consistent with the finding from a prior case-case study involving 1210 Chinese PCa patients [8]. SNP rs10069690, another susceptibility locus discovered by that study, however, was not confirmed in our study. In terms of prostate cancer-specific death, we first found a potential susceptibility locus (rs35812074) (p = 0.034). This SNP was reported to be associated with lung cancer by a recent GAWS [20]. However, the finding of rs35812074 in relation to PCa death in our study should be treated with caution because the risk allele of rs35812074 was detected as the major allele, and the minor allele frequency of this SNP was lower than 5%. Although the current imputation method ensures the imputation accuracy for the genotypes, result interpretation remains further validated in other GWASs and functional experiments.
In the present study, we found that most of the risk loci were located in intron regions, particularly intron 2 in both ancestries. Introns, at present, have been paid increasing regard to gene regulation, such as genome organization, transcription regulation, and alternative splicing [21]. The intron 2 of TERT has been presumed to harbor a putative regulatory region [22] and thus is likely to play a significant role in biological functions. As reported by prior functional studies involving polymorphisms in the intron 2 region of TERT, rs2853677 was found located within the Snail1 binding site in a TERT enhancer, the risk allele of which disrupted the Snail1 binding site, and the resultant derepressed TERT expression increased cancer susceptibility [23]. Confirmed by ex vivo luciferase gene assays, SNP rs2736100 was found situated at an intronic enhancer and could pose a genotype-specific impact on TERT expression [24].
Since promoter activity is essential for gene expression, the mechanisms between polymorphisms in the TERT promoter region and tumorigenesis merit further investigations. A previous functional investigation revealed that the switch with risk allele at TERT promoter variant (rs2853669) was pivotal in regulating TERT expression by influencing MYC and E2F1 expression. The resultant synergistic effects of MYC/E2F1/TERT expression with the rs2853669 polymorphism further deteriorated the prognosis of prostate cancer [25].
Two synonymous variants at the exon region of TERT were identified in this study. SNP rs2736098 was previously found located in an open chromatin region with gene regulatory elements and was reported to correlate with a higher prostate-specific antigen level [26]. The aberrant activation of the related transcriptional factors caused by the variation in this SNP may drive the potential signaling pathways of tumorigenesis [27]. Another synonymous SNP, rs35033501, was reportedly associated with splicing patterns alteration and cancer susceptibility increase by disrupting certain splice sites [28].
Our study identified several novel genetic variants of TERT in relation to PCa risk in different ancestries. In European ancestry, five novel SNPs involving intron 12, intron 9, intron 6, and intron 2 regions were discovered, while two novel SNPs situated at intron 2 were discovered in those of Chinese ancestry. This finding can strongly broaden the evidence base on the genetic predisposition of prostate cancer and can refine the genetic architectures of PCa susceptibility loci across the TERT region among distinct ancestries. One plausible explanation underlying the association between these novel SNPs and PCa risk may be attributable to a high linkage disequilibrium with adjacent polymorphisms with biological function.
This study supports the evidence of different genetic variants between Europeans and Chinese, which can furnish insights into public health practice, such as different population-based risk stratification and ethnic-specific target screening. According to the findings of our prior research, the precision of risk estimate decreased when applying European-specific PCa polygenic risk score as a risk stratification tool to other ancestry populations [29]. In addition, compared with the large sample size of European GWASs, the small sample size of the East Asian studies led to an imbalance in the risk variants identification and a decrease in the risk estimate precision in this group [30]. Therefore, it is necessary to identify more ethnic-specific risk variants in non-Europeans for a precisely targeted screening and early diagnosis.
There are several limitations in the present study. First, survival data are not available in the Chinese population. However, the Gleason score is associated with PCa survival which may provide some evidence. Second, gene-based analysis is estimated based on the germline loci, whereas the actual function of TERT in each individual is unclear. For example, the expression level of TERT from each participant is unable to be captured based on the gene-based analysis. Future studies in the biospecimen are considered to address this issue. Finally, subsequent functional experiments are warranted to assess the present findings, as well as to evaluate the different functions between the loci in promoter and intron 2 regions in the TERT.

Conclusions
In conclusion, this study, including a large set of SNPs and two ethnic populations, supports the existing evidence regarding TERT polymorphisms in relation to PCa risk and prognosis, discovers some novel PCa-related genetic variants in the TERT region, and indicates the heterogeneous genetic architectures of PCa susceptibility loci among distinct ancestries. Further functional studies of TERT polymorphisms are required to validate the present findings and reveal the underlying mechanisms. Funding: This work was supported by grants from the National Natural Science Foundation of China [grant number 81972645], an innovative research team of high-level local universities in Shanghai, the Shanghai Youth Talent Support Program, an intramural grant of The University of Hong Kong to Rong Na, and the Shanghai Sailing Program [grant number 22YF1440500] to Da Huang. All the funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Institutional Review Board Statement:
The study was conducted in accordance with the Declaration of Helsinki, and was approval by the Institutional Review Board of each hospital. Data of this study are secondary data from UK Biobank and ChinaPCa, whose ethnical approval information have been published in their research [10,12].
Informed Consent Statement: Informed consent has been obtained from all subjects in the UKB and ChinaPCa. Data Availability Statement: UKB Data used in this research are publicly available to qualified researchers on application to the UK Biobank (www.ukbiobank.ac.uk (accessed on 15 November 2022)). The study protocol, statistical analysis plan, and analytical code of this study will be available from the time of publication in response to any reasonable request to the corresponding author.